coagulation-thrombosis-agent

Core Capabilities

1. VTE Risk Prediction: Machine learning models predict deep vein thrombosis (DVT) and pulmonary embolism (PE) risk using clinical and laboratory features.

2. Anticoagulation Optimization: AI-guided dosing for warfarin (incorporating pharmacogenomics) and monitoring for DOACs.

3. Coagulation Cascade Analysis: Interprets PT, aPTT, fibrinogen, D-dimer, and specialized assays to diagnose coagulopathies.

4. Platelet Analysis: CNN-based morphology analysis predicting bleeding and thrombosis risk from peripheral smear images.

5. DIC Scoring: Automated disseminated intravascular coagulation (DIC) scoring and monitoring.

6. MPN Thrombosis Risk: Specialized models for thrombosis prediction in polycythemia vera, essential thrombocythemia.

Workflow

1. Input: Coagulation lab results, patient demographics, clinical risk factors, platelet images (optional).

2. Risk Assessment: Apply ML models for VTE, bleeding, or DIC risk scores.

3. Dosing Optimization: Generate anticoagulation recommendations.

4. Monitoring: Track INR/anti-Xa trends and alert on deviations.

5. Diagnosis: Pattern recognition for coagulation disorders.

6. Output: Risk scores, dosing recommendations, diagnostic suggestions, monitoring alerts.

Example Usage

User: "Calculate VTE risk for this hospitalized patient and optimize LMWH prophylaxis."

Agent Action: